面向新一代智能制造的人- 信息- 物理系统(HCPS)

ResearchIntelligent Manufacturing—PerspectiveHuman–Cyber–Physical Systems (HCPSs)in the Context of New-Generation IntelligentManufacturingZhou Ji a ,Zhou Yanhong b ,⇑,Wang Baicun c ,d ,⇑,Zang Jiyuan caChinese Academy of Engineering,Beijing 100088,ChinabHuazhong University of Science and Technology,Wuhan 430074,China cTsinghua University,Beijing 100084,China dUniversity of Michigan,Ann Arbor,MI 48109,USAa r t i c l e i n f o Article history:Received 3July 2019Revised 12July 2019Accepted 15July 2019Available online 22July 2019Keywords:New-generation intelligent manufacturing Human–cyber–physical system Human–physical system Cyber–physical system Knowledge engineering Enabling technologyManufacturing domain technology New-generation artificial intelligencea b s t r a c tAn intelligent manufacturing system is a composite intelligent system comprising humans,cyber sys-tems,and physical systems with the aim of achieving specific manufacturing goals at an optimized level.This kind of intelligent system is called a human–cyber–physical system (HCPS).In terms of technology,HCPSs can both reveal technological principles and form the technological architecture for intelligent manufacturing.It can be concluded that the essence of intelligent manufacturing is to design,construct,and apply HCPSs in various cases and at different levels.With advances in information technology,intel-ligent manufacturing has passed through the stages of digital manufacturing and digital-networked manufacturing,and is evolving toward new-generation intelligent manufacturing (NGIM).NGIM is characterized by the in-depth integration of new-generation artificial intelligence (AI)technology (i.e.,enabling technology)with advanced manufacturing technology (i.e.,root technology);it is the core driving force of the new industrial revolution.In this study,the evolutionary footprint of intelligent manufacturing is reviewed from the perspective of HCPSs,and the implications,characteristics,technical frame,and key technologies of HCPSs for NGIM are then discussed in depth.Finally,an outlook of the major challenges of HCPSs for NGIM is proposed.Ó2019THE AUTHORS.Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.This is an open access article under the CC BY-NC-ND license(/licenses/by-nc-nd/4.0/).1.IntroductionIntelligent manufacturing is a general concept that has been continuously evolving with the development and integration of information technology and manufacturing technology.In general,intelligent manufacturing has passed through the stages of digital manufacturing and digital-networked manufacturing,and is evolv-ing toward new-generation intelligent manufacturing (NGIM),due to the recent fast-paced development and influential break-throughs that have been occurring in the internet,big data,and artificial intelligence (AI)[1–14].Although the intelligent manufac-turing is constantly evolving [15–24],its fundamental goals remain the same:namely,to improve quality,increase efficiency,reduce costs,and enhance competitiveness through unrelenting efforts toward optimization.From the perspective of system constitution,an intelligent manufacturing system is always a human–cyber–physical system (HCPS)—that is,a kind of composite intelligent sys-tem comprising humans,cyber systems,and physical systems with the aim of achieving specific goals at an optimized level [25–28].In other words,the essence of intelligent manufacturing is to design,construct,and apply HCPSs in various cases at different levels.NGIM is characterized by the in-depth integration of new-generation AI technology with advanced manufacturing technol-ogy,and is the core driving force of the new industrial revolution.In order to promote the development of NGIM,this work presents an examination of the implications,characteristics,technical frame,and key technologies of HCPSs for NGIM,along with an out-look of the major challenges of HCPSs for NGIM.The rest of this paper is organized as follows:Section 2reviews the evolution and development of manufacturing systems,and Section 3analyzes the implications of HCPSs for NGIM from system and technology perspectives.A technical framework and key tech-nologies of HCPSs for NGIM are presented in Section 4.Finally,major challenges are outlined in Section 5.⇑Corresponding authors.E-mail addresses:yhzhou@ (Y.Zhou),wangbaicunzju@ (B.Wang).2.Evolution of HCPSs for intelligent manufacturing2.1.Phase I:Human–physical systems for traditional manufacturingHumansfirst learned to make and use tools more than two mil-lion years ago[29].Progressing from the Stone Age through the Bronze Age to the Iron Age,these early simple production systems lasted for over a million years,powered by human and animal labor.With the development of the First Industrial Revolution, which was marked by the invention of the steam machine,and the Second Industrial Revolution,which was marked by the inven-tion of the electric motor,humans have continually invented,cre-ated,and improved various machines and applied them to manufacture all kinds of goods[13].These traditional manufactur-ing systems,which were comprised of humans and physical machines,replaced a significant amount of manual labor and sub-stantially increased manufacturing quality,efficiency,and societal productivity.A traditional manufacturing system consists of two major com-ponents—namely,humans and physical systems such as machi-nes—and is therefore a human–physical system(HPS),as shown in Fig.1.In an HPS,physical systems,through which working tasks are completed,act as the‘‘executing body,”while humans are the ‘‘master.”Humans are both the creators of physical systems and the managers and users of physical systems.In an HPS,many of the activities required to complete the working tasks—such as per-ception,cognition,learning,analysis,decision-making,control,and operation—must be supplied by humans.For example,in machin-ing with traditional machine tools,operators must carefully observe,analyze,manipulate,and control the machining process.A general schematic of an HPS is shown in Fig.2.2.2.Phase II:HCPS1.0for digital manufacturingThe manufacturing sector entered the era of digital manufactur-ing in the middle of the20th century,driven by the development and wide application of information technologies including com-puters,communication,and numerical control[30–33].The infor-mation revolution,which was marked by digitalization,led and promoted the Third Industrial Revolution[34–36].Compared with traditional manufacturing systems,digital manufacturing systems are characterized by the emergence of a cyber system between the human and physical system,transforming the previous binary HPS into the ternary HCPS,as shown in Fig.3.A cyber system consists of software and hardware;its main function is to complete various tasks that were previously performed by human operators,including sensing,analysis,decision-making, and control.For example,in machining with a computer numerical control(CNC)machine tool,which is equipped with a cyber system called the CNC system,the CNC system can automatically direct the machine tool to complete the machining processes according to digital machining programs provided by the operators[37].Digital manufacturing can be defined asfirst-generation intelli-gent manufacturing,and the HCPS for digital manufacturing will be referred to herein as pared with the HPS,HCPS1.0has substantially enhanced capabilities—especially incomputation, Fig.1.An HPS for traditionalmanufacturing.Fig.2.Schematic of anHPS.Fig.3.HCPS1.0for digital manufacturing.J.Zhou et al./Engineering5(2019)624–636625analysis,precision control,and perception—due to its integration of the strengths of humans,cyber systems,and physical systems.The result is remarkable:Manufacturing systems based on HCPS1.0have significant improvements in aspects such as automation,efficiency,quality,stability,and the ability to solve complicated issues.In addition,not only can the manual labor of operators be further reduced,but also some of the mental work can be performed by cyber systems,thus effectively increasing the efficiency of knowledge dissemination and utilization.A schematic for HCPS1.0is shown in Fig.4.As shown in Fig.4,the upgrade from binary HPS to ternary HCPS generated two new binary subsystems:the human–cyber system (HCS)and the cyber–physical system (CPS)[26,38,39].The CPS the-ory was first proposed by American scholars at the beginning of the 21st century [40,41]and has been employed as a core technology of Industry 4.0in Germany [42,43].In addition,the introduction of cyber systems has fundamen-tally transformed the feature of machines by transforming them from unary physical systems to binary CPSs (i.e.,intelligent machi-nes).In this sense,the Third Industrial Revolution can be regarded as the beginning of the Second Machine Age [13].In the context of HCPS1.0,while physical systems continue to act as the ‘‘executing body,”cyber systems perform a significant amount of analysis,computation,and control work previously per-formed by humans.Humans are still the ‘‘master.”First,both phys-ical systems and cyber systems are designed and created by humans.The underlying analysis,computation and control models,methods,and rules are all developed by humans by drawing upon theoretical knowledge,experience,and experimental data and pro-gramming these into the cyber systems.In addition,the operation of HCPS1.0relies on the knowledge and experience of the operator to a significant extent [44].For example,when machining with CNC machine tools,as mentioned above,operators must program the machining process appropriately according to their knowledge and experience,monitor the process,and make adjustments where necessary.2.3.Phase III:HCPS1.5for digital-networked manufacturingBy the end of the 20th century,the rapidly developing internet technology had been widely applied to the manufacturing industry,driving a transformation from digital manufacturing to digital-networked manufacturing [17,45–47].Digital-networked manufacturing is,in essence,‘‘internet +digital manufacturing”and can be defined as second-generation intelligent manufactur-ing.The digital-networked manufacturing system remains an HCPS;however,it is referred to herein as HCPS1.5,since it has fun-damental differences compared with HCPS1.0for digital manufac-turing,as shown in Fig.5.The most significant difference lies in the cyber system.In the cyber system of HCPS1.5,the Industrial Inter-net and the cloud platform are critical components that can con-nect relevant cyber systems,physical systems,and humans,thus serving as a tool for system rmation exchange and coordinated and integrated optimization have become impor-tant parts of the cyber system.Meanwhile,the humans in HCPS1.5have become a network-connected community with common value-creation goals,and include the people from the enterprise hosting the system along with its suppliers,sales agents,cus-tomers,and so on.These changes transform the manufacturing industry,both from a product-centric model to a customer-centric model and from a production manufacturing pattern to a production–service manufacturing pattern.The essence of digital-networked manufacturing is the realiza-tion of extensive connections of humans,processes,data,and things through networks,and the reshaping of the manufacturing value chain through in-enterprise and inter-enterprise integration,cooperation,sharing,and optimization of various resources.For example,CNC machine tool manufacturers and their suppliers can engage in remote-operation maintenance of their ownproductsFig. 4.Schematic of HCPS1.0.HCS:human–cyber system;CPS:cyber–physicalsystem.Fig.5.HCPS1.5for digital-networked manufacturing.626J.Zhou et al./Engineering 5(2019)624–636through networks,in order to jointly create values with the enter-prises using their products.Enterprises using CNC machine tools can also create added value through the integration and optimiza-tion of in-enterprise sources regarding design,production,service, and management[37,48,49].2.4.Phase IV:HCPS2.0for NGIMModern manufacturing enterprises generally face strong demands for improvement in quality,efficiency,and quick market response.These demands have raised an urgent need for a revolu-tionary industrial upgrade for the manufacturing industry.On a technical level,it is still difficult for digital-networked manufactur-ing to overcome the huge difficulties faced by the manufacturing industry;thus,further manufacturing technology innovation and upgrades are greatly desired.Since the beginning of the21st century,huge progress has been made in information technologies such as the internet,cloud computing,and big data[12,50–52].The integration of these technological advances is leading to the strategic breakthrough of new-generation AI,which has become the core technology of a new round of scientific and technological revolution[2,5,53–55].The in-depth integration of new-generation AI technology with advanced manufacturing technology is leading to NGIM[1].Break-throughs and broad applications of NGIM will reshape the techno-logical architecture,production mode,and industrial pattern of the manufacturing industry.The information revolution,which is marked by AI,is leading and promoting the Fourth Industrial Revolution.The NGIM system remains an HCPS;however,it is referred to herein as HCPS2.0,since it has essential differences in comparison with HCPS1.5for digital-networked manufacturing,as shown in Fig.6.As in the shift from HCPS1.0to HCPS1.5,the most distinct changes occur in the cyber system.A new component is introduced to the cyber system of HCPS2.0,enabling it to perform self-learning and cognition by using new-generation AI technology;this leads to greater power in aspects such as perception,decision-making,con-trol,and—most importantly—the capability to learn and generate knowledge.The knowledge base in the HCPS2.0cyber system is jointly built by humans and by the self-learning and cognition module of the cyber system;thus,it contains not only the knowledge provided by humans but—more importantly—the knowledge learned by the cyber system itself,and particularly the knowledge that is difficult for humans to describe and process. Moreover,the knowledge base is able to constantly upgrade, improve,and optimize itself through self-learning and cognition during the application process.To use a metaphor,the relationship between humans and cyber systems has fundamentally changed from one of‘‘givingfish”to one of‘‘teaching how tofish”[1,2,6].A schematic of HCPS2.0is shown in Fig.7.HCPS2.0for NGIM can not only bring about revolutionary changes in the means and efficiency of creating,accumulating,uti-lizing,imparting,and inheriting manufacturing knowledge,but also significantly increase the ability of manufacturing systems to handle uncertain and complicated problems,thereby leading to vast improvements in manufacturing system modeling and decision-making.For example,in machining with intelligent machine tools,a digital model of the entire machining system can be built through sensing,learning,and cognition,and can then be used to optimize and control the machining process in order to obtain high machining quality and efficiency as well as low energy consumption[48,49,56].The role of humans as‘‘master”is even more prominent in HCPS2.0for NGIM[28,57–61].As the creators,managers,and oper-ators of intelligent machines,humans’abilities and skills will be greatly improved and their intellectual potential will be fully unleashed for further emancipation of the productive forces. Knowledge engineering will free humans from a significant amount of intellectual and manual labor and allow them to engage in more valuable creative work.In summary,intelligent manufacturing will better serve humans.Having evolved from HPS to HCPS1.0and then from HCPS1.0to HCPS1.5,intelligent manufacturing is evolving from HCPS1.5to HCPS2.0,and will advance stage by stage,spiraling up and expanding in an infinite process,as shown in Fig.8.3.Implications of HCPS2.0for NGIMHCPS2.0is a system architecture and technical framework for NGIM,which can offer a guide to effectively solve various problems in the upgrading of manufacturing industry.The implicationsof Fig.6.HCPS2.0for NGIM.J.Zhou et al./Engineering5(2019)624–636627HCPS2.0for NGIM may be described from both system and tech-nology perspectives.3.1.The system perspectiveHCPS2.0for NGIM is a composite intelligent system that com-prises relevant humans,AI-capable cyber systems,and physical systems,with the aim of achieving specific manufacturing goals at an optimal level.In this paradigm,physical systems,which exe-cute the energy and materialflows of manufacturing activities and complete the manufacturing tasks,act as the‘‘executing body.”AI-capable cyber systems act as the core of the informationflows of the manufacturing activities,and help humans to complete the necessary perception,cognition,analysis,decision-making,and control of the physical systems for their optimized operation. Humans play the role of the‘‘master”;they are the creators of physical systems and cyber systems,so the intelligence of cyber systems—no matter how powerful—comes from humans.In addi-tion,humans are the operators and users of physical systems and cyber systems,so humans remain in the central position and pos-sess the highest right to make decisions and enact control.HCPS2.0for NGIM should be geared to comprehensively upgrade all manufacturing activities,including research and devel-opment(R&D),production,sales,service,management,and system integration,in order to substantially increase quality,efficiency, and competitiveness.In other words,the essence of NGIM is to construct and apply different HCPS2.0systems serving different purposes and integrate them as a network of HCPS2.0systems in order to deliver a revolutionary improvement of societal produc-tivity.In general,HCPS2.0for NGIM possesses three main charac-teristics:intelligence,grand systems,and ubiquitous integration.First,intelligence is the primary characteristic of HCPS2.0for NGIM,as HCPS2.0systems can always keep their status and behav-ior optimal through autonomous learning and adjustment.Second,HCPS2.0for NGIM can establish grand systems through system integration.In general,HCPS2.0for a manufacturing enter-prise includes three functional systems—intelligent products,intel-ligent production,and intelligent services—and two supporting systems—the intelligent manufacturing cloud and the Industrial Internet[52,62,63].Third,HCPS2.0for NGIM presents the unprecedented feature of ubiquitous integration[4,64–66].From one perspective,internally dynamic integration in an enterprise is pursued forintelligentFig.8.Evolution of HCPS-based intelligentmanufacturing.Fig.7.Schematic of HCPS2.0.628J.Zhou et al./Engineering5(2019)624–636design,production,sales,services,and management processes, resulting in vertical integration.The Industrial Internet and the intelligent manufacturing cloud enable integration,sharing,collab-oration,and optimization among enterprises,resulting in horizon-tal integration.From another perspective,externally deep integration should be promoted between manufacturing,financial, and upstream and downstream industries.This integration will result in the new commercial co-development of service-oriented manufacturing and production-based services.In addition,NGIM has the potential to integrate with intelligent cities,intelligent transportation,intelligent healthcare,and intelligent agriculture to form a giant system of intelligent ecosystems—an‘‘intelligent society.”3.2.The technology perspectiveIn HCPS2.0,the cyber systems are equipped with powerful intelligence by leveraging new-generation AI,thereby enabling three major technological characteristics[6,67].Thefirst,most critical,characteristic is that the cyber systems have the ability to solve uncertain and complex problems;further-more,problem-solving methods shift from the traditional model of emphasizing causality to an innovative model of emphasizing cor-relation,and further toward an advanced model of deeply integrat-ing correlation with causality.This shift will lead to fundamental improvements in the modeling and optimization of manufacturing systems[5–7,13].The second most important characteristic is that the cyber sys-tems have capacities such as learning,cognitive skills,and the gene-ration and better utilization of knowledge[2,53–55,68–70];these will lead to revolutionary changes in the efficiency of knowledge generation,utilization,importation,and accumulation,and to the significant promotion of the marginal productivity of knowledge as a core productive element[2,53–55,68–70].The third characteristic is the formation of human–machine hybrid-augmented intelligence,which gives full scope to and synergistically integrates the advantages of human intelligence and machine intelligence.This will result in the innovation poten-tial of humans being fully unleashed and the innovation capacities of the manufacturing industry increasing tremendously[2,5,8].Overall,HCPS2.0is currently in the stage of weak AI or narrow AI(ability to accomplish a narrow set of goals,e.g.,play chess or drive a car)and will gain rapid development as AI advances from narrow AI to strong AI or general AI(ability to accomplish virtually any goal,including learning)[2,5,71].HCPS2.0can be regarded as a universal solution that will effec-tively solve the challenges occurring in the transformation and upgrading of the manufacturing industry,and that can be widely applied for product innovation,production innovation,and service innovation in discrete manufacturing and process-oriented manu-facturing.HCPS2.0is expected to progress as follows: HCPS2.0will enable manufacturing systems with new-generation AI technology.While there are many approaches to the innovation-driven development of manufacturing engineering, two are particularly important.Thefirst of these approaches is original innovation in manufacturing technology,which is funda-mental and of the utmost importance.The second approach is the application of common enabling technologies to promote manu-facturing technology,which can result in the development of innovative manufacturing technology through the integration of the two technologies,and which can be used to upgrade various manufacturing systems.This kind of innovation is revolutionary, integrative,and universal.The common enabling technologies of the last three industrial revolutions were the steam engine,electric motor technology,and digital technology,respectively;in the Fourth Industrial Revolution,the common enabling technology is AI technology[1].The in-depth integration of these generic enabling technologies with manufacturing technologies drives revolutionary transformation and upgrading of the manufacturing sector.Therefore,NGIM based on HCPS2.0will be the main driver of the innovation-driven development of the manufacturing sector and the main roadmap of its transformation and upgrading.However,new-generation AI technology must be thoroughly integrated with technologies in the manufacturing domain to cre-ate NGIM technologies.Because manufacturing is the foundation and enabling technologies are used to upgrade manufacturing, enabling technologies can give full scope only through in-depth integration with manufacturing technologies.To sum up,manufac-turing technologies are the fundamental technology,while intelli-gent technologies are the enabling technology;thus,there should be dialectical unity and integrative development between these technologies.From a perspective that focuses on intelligent tech-nology,NGIM can be seen as the endeavor to promote and apply advanced information technologies.From a perspective that focuses on manufacturing technology,however,NGIM can also be seen as the endeavor to employ generic enabling technologies to promote innovation in and the upgrading of manufacturing sys-tems in different industries.4.Technical framework of HCPS2.0for NGIM4.1.Overall architecture of HCPS2.0The overall architecture of HCPS for intelligent manufacturing can be described from the three dimensions of intelligent manufac-turing:the value dimension,the technical dimension,and the organizational dimension[72,73],as shown in Fig.9.4.1.1.The value dimension of intelligent manufacturing and the functional properties of the HCPSThe fundamental goal of intelligent manufacturing is to achieve value creation and value optimization by the construction and application of HCPSs.The value of intelligent manufacturing is mainly reflected in product innovation,intelligent production, intelligent services,and system integration[74,75],which corre-spond to product(R&D)HCPS,production HCPS,service HCPS, and integrated HCPS,respectively.When products are made to be digital,networked,and intelli-gent through innovation,their product functions andperformanceFig.9.Overall architecture of intelligent manufacturing based on HCPS.SoS: system of systems.J.Zhou et al./Engineering5(2019)624–636629are enhanced,which increases their added value and market com-petitiveness.Meanwhile,it is important to increase product quality and efficiency in product design by applying innovative processes via digital,networked,and intelligent technologies[76].Product innovations can be further divided into categories such as product design innovation,evaluation and validation innovation,and their integration.Product(R&D)HCPSs can likewise be further divided.Intelligent production will realize high-quality,flexible,effi-cient,and sustainable product manufacturing by comprehensively enhancing production and management innovation via digital,net-worked,and intelligent methods[75,77].In general,production activity can be divided into process design,process engineering, quality assurance,production management,and their integration. Some of these links can be further divided.For example,process engineering can be divided into multiple production lines and their integration,and a production line can be further divided into equipment and their integration.Likewise,production HCPSs can be further broken down into sub-layers.Intelligent services include user-centric services that are pro-vided throughout the life-cycle of products via digital,networked, and intelligent technologies[63,74,78,79];such services include customization and remote operation and maintenance,which extend to service-oriented manufacturing and production-based services.In this way,intelligent service HCPSs can be divided into customization service HCPSs and remote operation and main-tenance HCPSs,among others.As a key characteristic of NGIM,deep integration is an impor-tant aspect of the way in which NGIM delivers its value[4].Given the functional properties of HCPSs,their deep integration will lead to multifunctional,integrated,and complex HCPSs.4.1.2.The technical dimension of intelligent manufacturing and the technical properties of HCPSThe technology of intelligent manufacturing has evolved from digital manufacturing(HCPS1.0)to digital-networked manufactur-ing(HCPS1.5),and then to NGIM(HCPS2.0),as shown in Fig.10[1]. Digital manufacturing is the foundation of intelligent manufactur-ing,and has evolved through three basic paradigms.Digital-networked manufacturing provides the necessary network infras-tructure for intelligent manufacturing while integrating the busi-ness value chain.On the basis of previous two paradigms,NGIM makes manufacturing capable of true AI by integrating advanced manufacturing technology with new-generation AI technology and is a core technology of a new round of industrial revolution.The three basic paradigms of HCPS-based intelligent manufac-turing reflect the intrinsic patterns of the development of intelli-gent manufacturing.These three paradigms have unfolded progressively—each with its own characteristics and each solving problems in its respective stage—thus reflecting the progression of the integrated development of advanced information technology and manufacturing technology.However,the three basic para-digms are not entirely independent;rather,they are iterative and correlated with each other,thereby reflecting a fusion in the char-acteristics of intelligent manufacturing development[35].4.1.3.The organizational dimension of intelligent manufacturing and the systematic properties of HCPSThe organization of intelligent manufacturing consists of three levels—intelligent unit,intelligent system,and intelligent system of systems(SoS)—which correspond to unit-level HCPS,system-level HCPS,and SoS-level HCPS,respectively[39,80,81].An intelligent unit is the smallest functional unit of intelligent manufacturing.It is comprised of humans,cyber systems,and physical systems.An intelligent system integrates multiple intelli-gent units through the industrial network to achieve automated dataflow in a larger scope and across broader areas.It helps to improve the breadth,accuracy,and depth of manufacturing resource allocation across production lines,workshops,and busi-nesses to form a system-level HCPS.An intelligent SoS is a system that integrates multiple intelligent systems through Industrial-Internet-based integration across systems and platforms.It creates an open,coordinated,and shared industrial ecosystem,thus form-ing an SoS-level HCPS.The three-level architecture model of HCPS for intelligent manufacturing is shown in Fig.11.In summary,the overall architecture of HCPS2.0for NGIM can be described using the multi-level hierarchical structure shown in Fig.12.4.2.Key technologies of unit-level HCPS2.0For a unit-level HCPS2.0,regardless of its purpose(whether a design system,production equipment,etc.),the critical technolo-gies can be divided into the three categories of manufacturing domain technologies,machine intelligence technologies,and human–machine collaboration technologies,as shown in Fig.13.4.2.1.Manufacturing domain technologiesManufacturing domain technologies are the technologies involved in the physical systems of an HCPS;they include generic manufacturing technologies and specialized domain technologies [9].Intelligent manufacturing has its roots in manufacturing. Therefore,manufacturing technologies are a basic technology of HCPS for intelligent manufacturing.Meanwhile,intelligent manufacturing not only involves discrete manufacturingand Fig.10.Three basic paradigms of intelligent manufacturing[1].Fig.11.Three-level architecture model of HCPS for intelligent manufacturing. 630J.Zhou et al./Engineering5(2019)624–636。